Using Benefit-Cost Analysis to Protect the Environment

Increased use of Benefit-Cost Analysis (BCA) could either improve or harm the environment. As usual, the devil is in the details. Since the beneficial (=correct) use of BCA is readily achievable, the political momentum behind increased use of BCA should be seen as an opportunity to improve environmental decision-making. Lobbying efforts and political capital should be directed at appropriately defining BCA practices, and seeing to it that it is used in ways that are consistent with its capabilities. For environmentalists, the alternative is bleak. Opposition would consume more of their precious political capital, and it would give anti-environmentalists another sound-bite to use to attack productive, market mechanism-oriented environmental initiatives. Furthermore, since resisting the political momentum may be futile, incorrect, destructive uses of BCA might then predominate.

The justification for government intervention on behalf of the public’s interest in environmental values is that private decision makers will often lack incentives to properly take account of environmental factors in their deliberations. Under competitive pressures, they will ignore significant environmental costs and benefits. Our own history, and the environmental devastation evident in Eastern Europe and the countries of the former Soviet Union, proves that government decision makers may be even more prone to ignore them. Properly used, BCA can help prevent that by requiring that all effects of a project or regulatory decision be included in a readable, published evaluation.

Even in cases where a credible range of dollar values cannot be assigned to an expected effect (e.g. irreversibility concerns, species extinction risk, etc.), BCA can still inform decision makers and public debate, and make officials more accountable by correctly treating such unquantifiable (in $$) impacts as a subjective residual. For example, the BCA can say that benefits exceed costs only if decision makers think that one or more impacts that could not be quantified in $$ are valued more than $X. It could also show that it doesn’t matter. If quantifiable costs exceed quantifiable benefits, the decision being evaluated is inadvisable regardless of the value of unquantifiable costs.

Making policymakers adhere to rigorous definitions of Cost and Benefit, and making them carefully consider alternatives to traditional practices, are especially important outcomes of well-defined BCA practices. If the BCA examines several methods of intervention, the traditional command-and-control (CaC) approach will be chosen much less often. That is very important, because countless studies have shown that CaC approaches are inefficient, both in terms of excessive cost, and environmental results. The CaC approach’s impact on liberty and property rights creates public relations disasters that use up large amounts of environmentalists’ political capital.

Since BCA is about the dollar value of things that are likely to happen, it cannot ever absolutely “prove” anything. Assumptions may be violated, expected economic conditions may not be realized, and key inputs (numbers used to make benefit and cost calculations), such as discount rates and factors that determine the future dollar value of impacts, are controversial. To have any chance of approaching proof, and to insure that BCAs are always a valuable part of decision making processes, BCAs must include sensitivity analysis. Sensitivity analysis means that the BCA bottom line (Net Present Value [NPV] or Benefit-Cost Ratio) should be calculated for each of several reasonable values of key inputs used in the study. That improves BCA in several ways and it keeps officials from catering to special interests:

• Calculating a single NPV based on inputs and assumptions carefully selected to make the NPV appear favorable.
• Taking away their ability to ignore a BCA because one or a few of its inputs are vulnerable to criticism.

In many cases, sensitivity analysis will indicate that the results of a BCA are very robust. In other words, if the NPV is positive or negative over a very wide range of uncertain inputs, we will be as close as possible to “proof” that a decision is or is not in the public interest. If the results are not robust, the BCA would quite significantly indicate to officials, and the public, which factors the NPV estimates are particularly sensitive to. That could focus the public debate and officials on the key issues, make officials more accountable, and show us where additional research could perhaps narrow the range of critical uncertainties.

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